Evidence map›Paper›PMID 16504176›Full record

ArticleBMC genomics2006

Computational and experimental analysis identifies Arabidopsis genes specifically expressed during early seed development.

Cristian Becerra, Pere Puigdomenech, Carlos M Vicient

Open access · goldAbstract readValidation Study
In one paragraph

Article in BMC genomics, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
4.6field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed, 40 citations in OpenAlex.

  1. Article
  2. Article
  3. ArabidopsisInternational journal of molecular sciences · 2021
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  4. Review
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  6. Article
  7. Article
  8. Article
  9. Functions of the poly(ADP-ribose) polymerase superfamily in plants.Cellular and molecular life sciences : CMLS · 2012
    Review
  10. Article
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  12. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Cristian BecerraLaboratori de Genetica Molecular i Vegetal, CSIC-IRTA, Jordi Girona 18-36, 08034, Barcelona, Spain. cbbgmp@cid.csic.es
Pere Puigdomenech
Carlos M Vicient
Consejo Superior de Investigaciones Científicas · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPlant seeds are complex organs in which maternal tissues, embryo and endosperm, follow distinct but coordinated developmental programs. Some morphogenetic and metabolic processes are exclusively associated with seed development. The goal of this study was to explore the feasibility of incorporating the available online bioinformatics databases to discover Arabidopsis genes specifically expressed in certain organs, in our case immature seeds.

resultsA total of 11,032 EST sequences obtained from isolated immature seeds were used as the initial dataset (178 of them newly described here). A pilot study was performed using EST virtual subtraction followed by microarray data analysis, using the Genevestigator tool. These techniques led to the identification of 49 immature seed-specific genes. The findings were validated by RT-PCR analysis and in situ hybridization.

conclusionWe conclude that the combined in silico data analysis is an effective data mining strategy for the identification of tissue-specific gene expression.

Indexed as

Gene Expression ProfilingArabidopsisComputational BiologyExpressed Sequence TagsGene Expression Regulation, DevelopmentalGene Expression Regulation, PlantIn Situ HybridizationMutationPhenotypeReverse Transcriptase Polymerase Chain ReactionRNA, MessengerSeedsRNA, Messenger

Identifiers

PMID16504176
PMCPMC1420293
OpenAlexW1539962821

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.